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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Context Management & Reliability | 15% | - Long-context optimization
|
| Topic 2: Tool Design & MCP Integration | 18% | - Model Context Protocol (MCP)
|
| Topic 3: Agentic Architecture & Orchestration | 27% | - Agentic loop design and execution lifecycle
|
| Topic 4: Claude Code Workflows & Configuration | 20% | - Claude Code operational patterns
|
| Topic 5: Prompt Engineering & Structured Output | 20% | - Reliable structured generation
|
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NEW QUESTION # 82
Using the FastMCP Python SDK, which decorators are used to expose capabilities to an MCP client? Choose 2 correct answers.
Answer: A,C
Explanation:
The FastMCP Python SDK utilizes @mcp.tool to automatically generate JSON schemas for executable functions, and @mcp.resource to expose fetchable data endpoints. @mcp.agent and @mcp.action are not valid decorators in this SDK.
NEW QUESTION # 83
When implementing a hub-and-spoke multi-agent architecture using the Claude Agent SDK, which of the following statements about subagent spawning and execution are correct? Choose 2 correct answers.
Answer: B,D
Explanation:
To spawn subagents, the coordinator must be configured with 'Task' in its allowedTools. Furthermore, emitting multiple Task tool calls in a single response allows the subagents to execute their tasks in parallel. Subagents do not automatically inherit conversation history, and forcing sequential spawning is inefficient.
NEW QUESTION # 84
Which of the following statements represent correct principles of tool distribution and interface design? Choose 2 correct answers.
Answer: C,D
Explanation:
Proper tool distribution involves keeping tool counts low per agent by delegating to specialized subagents, and using highly detailed tool descriptions to define boundaries and prevent misrouting. Providing too many tools degrades accuracy, and tool_choice: "auto" allows the model to optionally bypass tools entirely.
NEW QUESTION # 85
Which of the following statements accurately describe the characteristics and constraints of the Message Batches API? Choose 2 correct answers.
Answer: B,C
Explanation:
The Message Batches API provides a 50% cost savings over synchronous calls and utilizes custom_id fields for request/response correlation. It does not provide latency SLAs (taking up to 24 hours) and is definitely not for real-time chatbot workloads.
NEW QUESTION # 86
A data extraction pipeline fails because the line items do not sum to the extracted total. How should the follow-up retry request be structured for the highest probability of success?
Answer: C
Explanation:
A successful validation-retry loop requires appending specific error details (e.g., 'Line items sum doesn't match subtotal') to the prompt and supplying both the source document and the failed extraction. Generic retry messages provide no signal for what to fix.
NEW QUESTION # 87
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